Researchers | LLMpeople

Lead research scientist at Ai2 and a founding member of the OLMo team. He works on open language models, language agents, evaluation, and reasoning, and helps build open-model research infrastructure.

Research scientist focused on machine learning and natural language understanding, with work spanning machine translation, semantic parsing, and large-scale language modeling.

Senior research scientist at Ai2 working on natural language processing, machine learning, and reasoning for the Aristo project; previously a researcher at the Institute for Natural Language Processing at the University of Stuttgart.

Researcher focused on computer vision, multimodal learning, and generative AI. His public homepage says he is currently with Stepfun, after serving as a principal scientist at SenseTime Research and a researcher at Microsoft Research Asia, and that he earned a PhD in computer science from Tsinghua University.

Yukun Zha is a research scientist at DeepSeek. His public profile lists research interests in machine learning, reinforcement learning, and efficient inference, alongside a PhD in computer science from Dartmouth College.

Research scientist and engineer focused on biomedical AI. He is a Member of Technical Staff at OpenAI, was previously a Research Scientist at Google DeepMind, and completed a Stanford PhD on accelerating biomedical intelligence.

Research scientist at Anthropic whose public work includes AI alignment, reinforcement learning from human feedback, and model behavior.

Computer scientist, UC Berkeley professor, and Databricks co-founder and CTO. He created Apache Spark and works on systems for large-scale data, machine learning, and compound AI applications.

PhD student at the University of Washington advised by Luke Zettlemoyer and researcher at Ai2. His work focuses on open language models, instruction tuning, data curation, and evaluation.

OpenAI researcher whose work spans alignment, machine learning, complexity science, open-ended evolution, and artificial life.

OpenAI researcher and engineer working on LLM reasoning; previously at Meta AI, DeepMind, and Jane Street.

Researcher at DeepSeek AI interested in generative models, large language models, multimodal learning, and computer vision. He is pursuing a PhD in electrical engineering at Stanford University after earning a bachelor's degree from Tsinghua University, and has also worked at Meta AI and Google.

AI researcher who co-created Sora at OpenAI and invented InstructPix2Pix during his PhD at Berkeley AI Research.

Research scientist at Tongyi Lab, Alibaba Group, working on multimodal large language models, machine reasoning, and efficient learning.

Research scientist at NVIDIA and University of Maryland PhD student whose public site highlights speech, audio, and video generation plus alignment for large language and vision-language models.

Research scientist at Google DeepMind focused on embodied AI and robotics. His homepage highlights work on skill acquisition, motion planning, world models, and imitation learning.

Researcher at Apple working on speech, audio, and multimodal machine learning; previously a senior research scientist at SRI International and also worked at Google.

PhD student in computer science at Peking University and research intern at PACMAN whose public homepage highlights computer systems, compilation, and parallel optimization for AI applications.

PhD student at the University of Chinese Academy of Sciences and researcher at BIGAI focused on reasoning, long context, and diffusion models; previously interned at DeepSeek, Microsoft Research Asia, and IDEA Research.

Assistant professor at Columbia University working on embodied AI, robot learning, world models, and computer vision. Previously a research scientist at Google DeepMind.

Junyang Lin (Justin Lin) is a researcher and open-source maintainer known for the Qwen family of models. His public profiles list interests in LLMs, AI agents, multimodal learning, long-horizon reasoning, world models, and reinforcement learning; multiple March 2026 news reports said he stepped down from the Qwen tech lead role.

Research scientist at Moonshot AI and postdoctoral scholar at Stanford University working on large reasoning models, reinforcement learning, and AI decision-making. He obtained a PhD in computer science from Arizona State University.

Nan Duan is head of foundation model post-training at Qwen and a vice president at Alibaba Group. His public profile highlights work on foundation models and natural language processing, after earlier research leadership at Microsoft Research.

Pradeep Dasigi is a senior research scientist at NVIDIA. His public profile notes previous work at the Allen Institute for AI and a PhD in computer science from the University of Pennsylvania, with research spanning NLP, semantic parsing, and knowledge graphs.

Senior applied scientist at NVIDIA working on open foundation models and post-training. Previously he was a visiting researcher at Google DeepMind and Google Brain, and he earned an MSc in computer science from ETH Zurich.

Researcher at Anthropic working on machine learning, language models, and reinforcement learning. Previously a postdoctoral researcher at Meta FAIR, and he earned a PhD in computer science from Harvard University.

Ilge Akkaya is a research scientist at OpenAI working on reinforcement learning and robotics. His personal website lists a PhD in EECS from UC Berkeley and a BS in Electrical and Electronics Engineering from Bilkent University.

Zihan Wang is a Northwestern University PhD candidate advised by Manling Li whose research focuses on agentic reinforcement learning, model efficiency, and long-context understanding. His official homepage lists prior internships at DeepSeek, Microsoft, and Yutori.

Engineer and product leader who worked on OpenAI's Applied AI team and now advises startups on AI products. He writes publicly about agents, retrieval, and evaluation on his personal site.

Algorithm Engineer at the Qwen Team, Alibaba Group. He received his Ph.D. in computer science from Beihang University in 2024 and works on post-training alignment for Qwen models, with research interests in large language models, graph neural networks, and recommender systems.

PhD student at Renmin University of China whose homepage highlights multimodal foundation models and video understanding, with public projects and papers including DeepSeek-VL and Kimi-VL.

Hang Zhu is a Research Scientist at ByteDance Seed focused on LLM infrastructure, including large-scale pre-training and post-training systems.

Renjie Zheng is a researcher at ByteDance. His public OpenReview profile lists prior research experience at Baidu Research and earlier study at Oregon State University and Tongji University, with public work spanning NLP, language models, and reasoning-related research.

Yuwen Xiong is a Research Scientist at ByteDance Seed in the Bay Area. He received a Ph.D. from the University of Toronto's Machine Learning Group and previously worked at Waabi and Uber ATG.

Adria Garriga-Alonso is a research scientist at Google DeepMind focused on machine learning and AI safety. His public profile notes a PhD in computer science from the University of Cambridge in 2020.

Research scientist at OpenAI working on AI agents, large models, and reinforcement learning. Previously worked as an applied scientist at Uber and completed a PhD in computer science at ENS Paris-Saclay under Marc Schoenauer and Olivier Teytaud.

Zhen Ye is a researcher in the Qwen team at Alibaba Cloud. His public profile notes a PhD in computer science from the University of Massachusetts Amherst and research interests in natural language understanding, generation, and reasoning.

Ksenia Konyushkova is a research scientist at Google DeepMind in London working on computer vision and embodied AI. Before DeepMind, she co-founded Microverses and held postdoctoral roles at Imperial College London and UC Berkeley. She earned her PhD from EPFL under Pascal Fua.

Postdoctoral researcher at the Allen Institute for AI and the University of Washington whose work focuses on open language model post-training, steerability, and evaluation.

Researcher at Moonshot AI focused on multimodal large language models, visual reasoning, and understanding, with publications in major computer vision and machine learning venues.

Postdoctoral associate at MIT CSAIL working at the intersection of machine learning and healthcare. He earned a PhD in computer science from Cornell University and studies multimodal medical AI.

Research scientist at Google Research in New York City. He earned a PhD in computer science from NYU Tandon and works on language models, multimodal learning, NLP, and deep learning.

Yiheng Xu is a research scientist focused on multimodal AI, coding agents, and reasoning systems. His public profiles link him to Qwen research and later work at OpenAI, with publications spanning vision-language models and code generation.

Feida Zhu is a ByteDance researcher in computer vision. Public sources show prior roles at Tencent Youtu Lab and Nanyang Technological University, and a PhD in Computer Science from The University of Hong Kong.

Public sources identify Can Huang as a ByteDance researcher. OpenReview lists prior research work at Intsig Information Co. Ltd., master's study at Shanghai Jiao Tong University, and undergraduate study at Xi'an Jiaotong University.

Weihao Yu is a researcher in computer vision, multimodal AI, and neural architecture design. Public profiles show PhD and postdoctoral work at the National University of Singapore, a 2025 Research Scientist role at ByteDance Seed, and a 2026 appointment at Peking University Shenzhen Graduate School.

Xiangpeng Wei is an algorithm engineer at ByteDance Seed whose public research profile spans large language models, multimodal applications, and multilingual NLP.

Research scientist in Tongyi Lab whose official profile highlights large language models, multimodal foundation models, and AI agents.

Yong Shan is a ByteDance researcher whose public profiles and publication record indicate work across LLMs, neural machine translation, dialogue systems, and music generation.

Xin Hu is a Member of Technical Staff at OpenAI focused on privacy and security. Xin previously held cybersecurity and machine learning roles at Robinhood, Pinterest, IBM Research, and Intel, and earned a PhD in Computer Science and Engineering from the University of Michigan.

Bowen Yu is an Algorithm Expert at Qwen (Alibaba Group) working on LLM post-training and automated alignment.

Postdoctoral research scientist at Google Research working on machine learning for healthcare, medical imaging, and responsible AI.

Research scientist at OpenAI working on intelligent agents, computer vision, natural language processing, and robotics; he previously completed a PhD in computer science at Penn State.

Researcher working on machine learning systems and infrastructure at OpenAI. He earned his PhD from UCLA.

AI safety researcher and engineer; former OpenAI employee, founder and AI advisor at Metaculus, and creator of the CosmoTransitions package.

Shengding Hu is a final-year PhD student in the Department of Computer Science and Technology at Tsinghua University. His public homepage describes research on scalable pretraining, reinforcement learning, world models, large language models, and embodied agents.

Head of AI at Google Health in London and a practising NHS vascular surgeon whose work focuses on safe, effective and equitable medical AI.

Research scientist at OpenAI whose public profiles describe work on generative AI and reinforcement learning, after PhD study at the University of Cambridge.

Research scientist at Moonshot AI studying scaling in reinforcement learning and large language models.

Jian-Hui Duan is an algorithm researcher in the ByteDance Seed LLM team whose public homepage highlights work on pretraining data, training optimization, and distribution-shift mitigation for large language models.

Xinxing Zu is a research scientist at Moonshot AI. His public profile notes a PhD in computer science from New York University, prior work as an AI scientist at Amazon, and research interests in AI agents, reasoning, and multimodality.

Rui Qian is a researcher at ByteDance Seed. Qian received a Ph.D. from The Chinese University of Hong Kong and a bachelor's degree from Shanghai Jiao Tong University in 2021.

Public profiles and publication indexes link Xingyan Bin to ByteDance research work and Tsinghua University, with papers in recommendation, retrieval, MoE models, and LLM pre-training/quantization.

Yujia Qin focuses on LLM/VLM-based agents. The official homepage lists a Ph.D. in Computer Science from Tsinghua University (2020-2024), a B.E. in Electronic Information Science and Technology from Tsinghua University (2016-2020), and Seed at ByteDance starting in July 2024.

Zhiqi Lin is publicly listed on OpenReview as a researcher at ByteDance Inc. OpenReview also lists prior computer science study at the University of Science and Technology of China, with undergraduate study from 2015 to 2019 and PhD study from 2019 to 2024.

Research scientist at NVIDIA working on compression, efficient inference, post-training, multimodality, and evaluation for large language models. He completed a PhD in machine learning at Stanford and a master's in artificial intelligence at the University of Edinburgh.

Research scientist at OpenAI whose public profiles highlight multi-agent alignment, scalable training, and reinforcement learning.

Leon Derczynski is a professor in natural language processing at DTU Compute whose research focuses on information extraction, online harms, and the dynamics of abusive language and misinformation.

Resident at xAI and long-term visitor at the Center for AI Safety. He recently completed a PhD in electrical and computer engineering at the University of Texas at Austin, and his work is grounded in mathematical and statistical machine learning plus control theory.

Juntang Zhuang is a research scientist at OpenAI working on multimodal learning and diffusion models. His public profile notes a PhD in computer science from UC Berkeley and earlier research internships at Google DeepMind and Microsoft.

Xingcheng Yao is a research scientist at Moonshot AI. His public profile notes prior work as a research engineer at Tencent AI Lab, a PhD in computer science from the University of Southern California, and research interests spanning NLP, multimodal systems, and AI agents.

Guanghan Ning is a ByteDance researcher whose public homepage says he switched to foundation models at the beginning of 2023, especially code LLMs, after earlier work in computer vision and deep learning.

Qi Liu is a ByteDance researcher whose public OpenReview profile lists prior research work at Horizon Robotics and studies at Fudan University and Huazhong University of Science and Technology. Public expertise areas include multimodal large language models, gesture recognition, metric learning, and deep learning.

Qiyang Min is a researcher at ByteDance Inc. whose public profiles and publication record indicate work on large language models, memory-augmented architectures, and related model systems. OpenReview lists prior research experience at Baidu and undergraduate study in software engineering at Nanjing University.

Public profiles identify Shihan Dou as a PhD student at Fudan University. His publication record covers LLM alignment and reward or preference modeling, with additional work on code intelligence and document parsing.

Yifan Du is a Ph.D. student at Renmin University of China advised by Wayne Xin Zhao. His public homepage lists research interests in multimodal large language models, visual instruction tuning, long video understanding, and complex visual reasoning, and it lists a VLM post-training internship at ByteDance Seed.

Yufei Guo is an assistant professor in the UCLA Computer Science Department. His public profiles note prior work as a research scientist at OpenAI and research interests in AI agents, reinforcement learning, and large language models.

Member of technical staff at OpenAI working on alignment. Previously worked at Google, DeepMind, and Meta, and completed a PhD in neuroscience at Oxford.

Head of AI at Cohere and professor at the University of Pennsylvania whose public profiles focus on natural language understanding, reasoning, and grounding.

Research scientist at Google DeepMind working on trustworthy deep learning, multimodal modeling, and generalization in AI systems.

Mitesh M. Khapra is a professor at IIT Madras and co-founder of AI4Bharat whose research spans natural language processing, machine learning, transfer learning, and deep learning.

Chenwei Lou is a researcher at ByteDance Seed. Public profiles indicate earlier research experience at Tencent, an MS period at Harbin Institute of Technology, and earlier undergraduate study at Jilin University.

Trung H. Bui is a staff researcher at Cohere working on generative AI, large language models, natural language processing, machine learning, and computer vision.

Alec Radford is a researcher and a co-author of the GPT-4 Technical Report. His GitHub profile links to his personal website at newmu.github.io.

Seungyoun Hong is a research scientist and postdoctoral scholar at Stanford University working on machine unlearning, data attribution, hallucination, and generalization.

Chao Zhang is an applied scientist in the Alibaba Foundation Model team. His public profile notes a PhD in computer science from the University of Illinois Urbana-Champaign and research interests in NLP, large language models, reasoning, and multimodal generation.

Jiangjie Chen is a researcher at ByteDance Seed. He earned a Ph.D. in computer science from Fudan University in 2024 and works on reasoning models, autonomous agents, and machine reasoning.

MS student at Peking University's Wangxuan Institute of Computer Technology working on visual reasoning, VLM, OCR, and handwritten mathematical expression recognition.

Qiying Yu is a PhD student at the Institute for AI Industry Research (AIR), Tsinghua University, working on self-supervised learning and multimodal large models.

Chenhui Gou is a PhD student at Monash University in the Vision & Language for Autonomous AI Group. Public profiles list his research in computer vision, visual perception, and reasoning, following earlier master's study at the Australian National University.

Tenglong Ao is a computer science researcher whose public work focuses on character animation, co-speech gesture generation, music-driven dance generation, and multimodal agent behavior. Public sources indicate he received a Ph.D. in computer science from Peking University and a B.S. in electronic engineering from Tsinghua University.

Yongfei Liu is a researcher whose public profiles list interests in CodeLLM, generative multimodality, and vision-language research. His homepage says he completed a joint PhD program at the University of Chinese Academy of Sciences and ShanghaiTech University in 2022 after a bachelor's degree from Xidian University in 2017.

Ziheng Jiang is an AI researcher working on large language models and machine learning systems. His public homepage says he is a Principal AI Researcher at Meta and previously was a Principal Research Scientist at ByteDance.

Zilong Huang is a principal researcher at Tencent Singapore whose work focuses on multimodal interaction, multimodal agents, multimodal pretraining, and efficient model architectures. He previously worked at ByteDance and received his Ph.D. and B.E. from Huazhong University of Science and Technology.

Bencheng Liao is a PhD student at the Institute of Artificial Intelligence, Huazhong University of Science and Technology. Public profiles list research interests including autonomous driving, object detection, and visual perception.

Haobin Jiang is a Peking University PhD student whose public profiles describe research in reinforcement learning, robotics, and LLM post-training.

Joya Chen is a final-year Ph.D. candidate at Show Lab, National University of Singapore, advised by Mike Zheng Shou. Her research focuses on large multimodal models for video, including data scaling, model architecture, pre-training, post-training, and benchmarking.

Qingping Yang / 杨清平 is a researcher whose public homepage highlights work on LLMs, especially code generation, table understanding, and structured information extraction. Public sources also connect him to earlier table understanding publications and recent reinforcement-learning-for-LLMs work.

Public sources connect Renrui Zhang to multimodal large language models, 3D point cloud analysis, and efficient model adaptation.

Rui Yang is a PhD student at The University of Hong Kong. Public OpenReview and DBLP records link him to research on multimodal large language models, language agents, and vision-language systems, including GPT4Tools, HaploVL, and Visual Spatial Tuning.

Siyu Yuan is a final-year Ph.D. student at Fudan University advised by Deqing Yang and Yanghua Xiao, working on reasoning models and autonomous agents.

Weinan Dai is a PhD student in Computer Science and Technology at Tsinghua University. Public profiles and publications link him to research on large language models, reasoning, and reinforcement learning, including Seed1.5-Thinking, DAPO, MemAgent, and Enigmata.

Yining Ye (叶奕宁) is a master's student in the THUNLP Lab at Tsinghua University advised by Zhiyuan Liu. Public profiles describe research on LLM/VLM agents, tool learning, and unified language models.

Yurui Ren is a researcher working on image/video synthesis and image enhancement. Public sources identify him as a Ph.D. student at Peking University (2017-2022), advised by Ge Li, with a B.S. from Dalian University of Technology.

Robotics researcher and co-founder of Physical Intelligence, previously an assistant professor at USC and formerly at Google Brain, working on learning-based robot decision making and control.

Zhengyuan Liu is a research scientist at Alibaba Group and a PhD student at the National University of Singapore. His public profile highlights work in natural language processing, vision-language models, and grounding.

Public sources associate Zewei Sun with ByteDance and list Nanjing University education (BS 2013-2017, MS 2017-2020), with research spanning machine translation and later large language model work.

Yufeng Yuan is listed on OpenReview as staff at ByteDance Seed, previously at Tencent AI Lab, with an MS in Computing Science from the University of Alberta.

Technical staff member on Moonshot AI's agent team whose public OpenReview profile lists work across deep learning, natural language processing, large language models, vision-language models, and agents.

Public records identify Xuefeng Xiao as a ByteDance-affiliated researcher whose work centers on model compression, optimization, and acceleration; his OpenReview profile also lists M.S. study at South China University of Technology.

Junting Lu is a final-year M.S. student at the Institute for Software Engineering, Peking University. His homepage lists research interests in tool learning, OS agents, and native vision-language agents.

Ning Dai is a PhD student in EECS at Oregon State University. His public OpenReview profile includes ByteDance Seed's Seed1.5-Thinking report and lists expertise in code generation, post-training for LLMs, and RNA design.

Xinchen Zhang is a master's student at Tsinghua University and a research intern at ByteDance Seed. His public profiles describe research on multimodal large language models, reinforcement learning for multimodal post-training, and earlier work on diffusion-based text-to-image generation.

Yao Luo is an LLM researcher at the ByteDance Seed Team. Her public homepage lists research interests in sparse architectures, linear attention, long-context modeling, and model merging.

Assistant professor in the University of Pennsylvania Department of Computer and Information Science whose research spans natural language processing, speech, and multimodal learning; previously a research scientist at Facebook AI Research.

Research scientist at Cohere Labs and PhD candidate at Stanford University focused on language models, machine learning systems, and AI safety.

Research scientist working on large-scale deep learning for speech translation, spoken language understanding, question answering, healthcare, and multimodal models.

Technical staff member at OpenAI working on large language models. Previously worked on Siri at Apple, and graduated from Carnegie Mellon University.

Senior algorithm expert at Alibaba Group working on large language models, multimodal large language models, and diffusion models.

Joshua (Josh) Achiam is Chief Futurist at OpenAI. He joined OpenAI in 2017 as a research scientist and has worked on AI safety research and operations, AI impacts research, and educational resources (including Spinning Up in Deep RL).

Luca Soldaini

Radu Soricut

Kyle Richardson

Jifeng Dai

Yukun Zha

Khaled Saab

Liane Lovitt

Matei Zaharia

Hamish Ivison

Joost Huizinga

Shantanu Jain

Sifan Zhou

Tim Brooks

Xinyu Zhang

Kaustubh Jha

Tianhe Yu

Asterios Katsamanis

Jiuzheng Wang

Tong Wu

Yunzhu Li

Junyang Lin

Dunyuan Zha

Nan Duan

Pradeep Dasigi

Utku Evci

David Brandfonbrener

Ilge Akkaya

Zihan Wang

Shyamal Anadkat

Le Yu

Haoyu Lu

Hang Zhu

Renjie Zheng

Yuwen Xiong

Adrià Garriga-Alonso

Adrien Ecoffet

Zhen Ye

Ksenia Konyushkova

Valentina Pyatkin

Dinglu Wang

Tiam Jaroensri

Siddhartha Brahma

Yiheng Xu

Feida Zhu

Can Huang

Weihao Yu

Xiangpeng Wei

Xiaohuan Zhou

Yong Shan

Xin Hu

Bowen Yu

Mercy Asiedu

Tao Xu

Tomer Kaftan

Carroll Wainwright

Shengding Hu

Alan Karthikesalingam

Raphael Ho

Hao Zhang

Jianhui Duan

Xinxing Zu

Rui Qian

Xingyan Bin

Yujia Qin

Zhiqi Lin

Trevor Gale

Jerry Tworek

Leon Derczynski

Brandon McKinzie

Juntang Zhuang

Xingcheng Yao

Guanghan Ning

Qi Liu

Qiyang Min

Shihan Dou

Yifan Du

Yufei Guo

Arka Dhar

Dan Roth

Evgenia Rusak